Instructions to use mlabonne/drllama-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlabonne/drllama-7b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mlabonne/drllama-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mlabonne/drllama-7b")
model = AutoModelForCausalLM.from_pretrained("mlabonne/drllama-7b")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mlabonne/drllama-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlabonne/drllama-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlabonne/drllama-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mlabonne/drllama-7b

SGLang

How to use mlabonne/drllama-7b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mlabonne/drllama-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlabonne/drllama-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mlabonne/drllama-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlabonne/drllama-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mlabonne/drllama-7b with Docker Model Runner:
```
docker model run hf.co/mlabonne/drllama-7b
```

drllama-7b

Commit History

Adding `safetensors` variant of this model (#1)

7337a78
verified

mlabonne

SFconvertbot commited on Apr 4, 2025

Upload tokenizer

6a43af6

mlabonne commited on Sep 10, 2023

Upload LlamaForCausalLM

4977710

mlabonne commited on Sep 10, 2023

initial commit

60016f7

mlabonne commited on Sep 10, 2023

Commit History

Adding `safetensors` variant of this model (#1) 7337a78 verified

Upload tokenizer 6a43af6

Upload LlamaForCausalLM 4977710

initial commit 60016f7

Adding `safetensors` variant of this model (#1)

7337a78
verified

Upload tokenizer

6a43af6

Upload LlamaForCausalLM

4977710

initial commit

60016f7